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These feature articles are published monthly by Quality Digest. They are collected under the nom de plume of The Six Sigma Heretic, which tells you something about how we approach Six Sigma. They are written by ROI President Steven Ouellette, and have a unique blend of humor and statistical depth that makes him one of Quality Digest's most popular authors. Subscribe to our RSS Feed to be alerted about each month's article!

Does this data make my shape look funny?

If you have been following my articles over the last few months, you have seen that even though statistical process control (SPC) charts are very powerful tools for examining a process, it turns out that there are a lot of ways to mess up SPC. This month, I am going to finish up with a few more things to watch out for as you use them, so you never have to ask, “Why doesn’t SPC work here?”

The chart isn't strange, it's just misunderstood.

Over the past couple of articles, we have explored how an incomplete understanding of how SPC limits are calculated can lead to constructing control charts that look strange. But using some of the things I mentioned, hopefully you can see that these “strange” control charts actually reveal quite interesting information about what is going on (and what to do about it). In the last article I left you with a weird looking control chart to see if you could figure out what was going on in the process. Instead of throwing out the chart and concluding that “SPC doesn’t work here,” let’s take a look at that and see what we could have learned about the process.

To err is human, but to really mess things up you need a statistician.

Have you ever met people who “do” statistical process control (SPC) only to get some screwy-looking control chart, and then text: OMG I H8 SPC! (If you don’t understand that, ask your nine-year-old child or grandchild.)

Last month we saw how it is not a failure of SPC, but rather an EBKAC (error between keyboard and chair). As I wrote in my last article, “Why Doesn't SPC Work?” perhaps they are not doing the measurement system analysis first, or perhaps autocorrelation in a continuous process. But you batch process folks are not off the hook, which is what this month’s article is about.

To err is human, but to really mess things up you need a statistician…

One of the most useful diagnostic tools for understanding what is going on in a process is the statistical process control chart (SPC). This is also a frequently misunderstood tool, and these misunderstandings lead to misdirected effort during a Six Sigma process, resulting in lost time and money. All the questions related to these foiled efforts boil down to this, “I used my software to make a control chart, but the chart looks all messed up. Why doesn’t SPC work?”

It does, if you avoid some common pitfalls. So today, I am kicking off a few articles about these pitfalls that I hope will make your projects less frustrating and more efficient.

Statistics from end to beginning

A colleague of mine made an interesting point about how we teach and learn experimental design techniques, and I thought I'd explore the subject further. He observed that the order that we teach statistics is almost exactly opposite of how one would actually use them. So this month I will describe the different tools and how they would be used in the actual order you might use them.